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Mortality models and longevity risk for small populations

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  • Wang, Hsin-Chung
  • Yue, Ching-Syang Jack
  • Chong, Chen-Tai

Abstract

Prolonging life expectancy and improving mortality rates is a common trend of the 21st century. Stochastic models, such as Lee–Carter model (Lee and Carter, 1992), are a popular choice to deal with longevity risk. However, these mortality models often have unsatisfactory results for the case of small populations. Thus, quite a few modifications (such as approximation and maximal likelihood estimation) to the Lee–Carter can be used for the case of small populations or missing observations. In this study, we propose an alternative approach (graduation methods) to improve the performance of stochastic models.

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  • Wang, Hsin-Chung & Yue, Ching-Syang Jack & Chong, Chen-Tai, 2018. "Mortality models and longevity risk for small populations," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 351-359.
    • Handle: RePEc:eee:insuma:v:78:y:2018:i:c:p:351-359
    DOI: 10.1016/j.insmatheco.2017.09.020
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    Cited by:

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    3. Bozikas, Apostolos & Pitselis, Georgios, 2020. "Incorporating crossed classification credibility into the Lee–Carter model for multi-population mortality data," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 353-368.
    4. Massimiliano Menzietti & Maria Francesca Morabito & Manuela Stranges, 2019. "Mortality Projections for Small Populations: An Application to the Maltese Elderly," Risks, MDPI, vol. 7(2), pages 1-25, March.

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